Logic at the Edge

Edge Computing for the Industrial Environment

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Do More on the Edge

The edge of the network consists of devices that form the backbone of the IIoT (Industrial Internet of Things). These edge devices, such as sensors, valves, pumps, or field devices are increasingly connected, “smart” equipment, that enable information to be processed where things and/or people create or use it i.e. the edge.

Historically, it was generally only possible to aggregate and read data from the edge but was much more difficult to implement a bidirectional flow of information. With AVEVA, it’s possible to do so much more at the edge, like perform logic directly, remotely manage a fleet of edge devices, or filter data from the edge through the systems that can use it to make intelligent decisions.

Edge computing can be a smart way to approach an edge to enterprise architecture, which leverages the value of performing logic on the edge and managing edge devices, but is able to scale up to include HMI, SCADA, and enterprise-level solutions for data with bidirectional communication with the cloud for a fuller picture of a business.


AVEVA Edge Management

Manage and provision devices and software at the edge

The Value of the Edge

The ability to read and write data to the edge of the network offers new capabilities that greatly enhance the power of IIoT architectures.


Remotely manage fleets of edge devices

AVEVA offers the ability to manage and control edge devices from the cloud using AVEVA Edge Management. Update multiple devices with new versions of software, manage revision control, or bring data from the edge into the cloud for analysis and action. Improve your ability to upgrade edge devices and sustain applications on the edge.


Enable Edge Control

Control solutions at the edge are possible with platform agnostic software solutions that are able to effectively run on edge devices, which typically do not share the same operating systems and protocols and require a much smaller footprint. Edge software solutions capable of running on low-end devices operating on Linux and equipped with emerging edge standard protocols like MQTT and OPC UA offer much more flexibility in successfully integrating edge devices into the network.


Reduce latency and filter data

Performing logic directly at the edge can greatly reduce the strain on a network. Small-footprint applications running directly at the edge can also reduce latency and improve the speed of data analysis. By collecting data directly at the edge, it’s also easier to filter information at the source and improve the quality of data sent to the cloud.


Improve security and reliability

More connected points can introduce security risks, but there are advantages as well. While a centralized source of data can represent a single target, a distributed edge solution makes it much more difficult to attack a single point. Distributed edge computing can also improve system reliability, as more functions are performed natively on devices.

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